



'''simple docstring'''






import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase:   str					=		get_tests_dir('fixtures/test_sentencepiece.model')

@require_sentencepiece
@require_tokenizers
class 				a__(   lowerCamelCase__						,					unittest.TestCase      ):
    lowercase__					=       ReformerTokenizer
    lowercase__					=       ReformerTokenizerFast
    lowercase__					=       True
    lowercase__					=       False
    lowercase__					=       True







    def      lowercase_			( self					:    List[str]      ):
      super().setUp()

      a		:   Any	  =	ReformerTokenizer(__snake_case		,     keep_accents=__snake_case      )
      tokenizer.save_pretrained(self.tmpdirname      )







    def      lowercase_			( self					:    Dict      ):
      a		:   Optional[Any]	  =	'<s>'
      a		:   Dict	  =	1

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(__snake_case      )		,     __snake_case      )
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(__snake_case      )		,     __snake_case      )







    def      lowercase_			( self					:    Optional[Any]      ):
      a		:   int	  =	list(self.get_tokenizer().get_vocab().keys()      )

      self.assertEqual(vocab_keys[0]		,     '<unk>'      )
      self.assertEqual(vocab_keys[1]		,     '<s>'      )
      self.assertEqual(vocab_keys[-1]		,     'j'      )
      self.assertEqual(len(__snake_case      )		,     10_00      )







    def      lowercase_			( self					:    int      ):
      self.assertEqual(self.get_tokenizer().vocab_size		,     10_00      )







    def      lowercase_			( self					:    Tuple      ):
      if not self.test_rust_tokenizer:
        return

      a		:   Any	  =	self.get_tokenizer()
      a		:   Any	  =	self.get_rust_tokenizer()

      a		:   str	  =	'I was born in 92000, and this is falsé.'

      a		:   List[str]	  =	tokenizer.tokenize(__snake_case      )
      a		:   List[Any]	  =	rust_tokenizer.tokenize(__snake_case      )
      self.assertListEqual(__snake_case		,     __snake_case      )

      a		:   Tuple	  =	tokenizer.encode(__snake_case		,     add_special_tokens=__snake_case      )
      a		:   Union[str, Any]	  =	rust_tokenizer.encode(__snake_case		,     add_special_tokens=__snake_case      )
      self.assertListEqual(__snake_case		,     __snake_case      )

      a		:   Tuple	  =	self.get_rust_tokenizer()
      a		:   List[str]	  =	tokenizer.encode(__snake_case      )
      a		:   List[Any]	  =	rust_tokenizer.encode(__snake_case      )
      self.assertListEqual(__snake_case		,     __snake_case      )







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    Tuple=15      ):
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""      ):
          a		:   Optional[Any]	  =	self.rust_tokenizer_class.from_pretrained(__snake_case		,     **__snake_case      )

          # Simple input
          a		:   Any	  =	'This is a simple input'
          a		:   Dict	  =	['This is a simple input 1', 'This is a simple input 2']
          a		:   List[Any]	  =	('This is a simple input', 'This is a pair')
          a		:   Optional[int]	  =	[
              ('This is a simple input 1', 'This is a simple input 2'),
              ('This is a simple pair 1', 'This is a simple pair 2'),
          ]

          # Simple input tests
          self.assertRaises(__snake_case		,     tokenizer_r.encode		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'      )

          # Simple input
          self.assertRaises(__snake_case		,     tokenizer_r.encode_plus		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'      )

          # Simple input
          self.assertRaises(
              __snake_case		,     tokenizer_r.batch_encode_plus		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'		,     )

          # Pair input
          self.assertRaises(__snake_case		,     tokenizer_r.encode		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'      )

          # Pair input
          self.assertRaises(__snake_case		,     tokenizer_r.encode_plus		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'      )

          # Pair input
          self.assertRaises(
              __snake_case		,     tokenizer_r.batch_encode_plus		,     __snake_case		,     max_length=__snake_case		,     padding='max_length'		,     )







    def      lowercase_			( self					:    str      ):
      pass







    def      lowercase_			( self					:    List[Any]      ):
      a		:   List[str]	  =	ReformerTokenizer(__snake_case		,     keep_accents=__snake_case      )

      a		:   Any	  =	tokenizer.tokenize('This is a test'      )
      self.assertListEqual(__snake_case		,     ['▁This', '▁is', '▁a', '▁t', 'est']      )

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(__snake_case      )		,     [2_85, 46, 10, 1_70, 3_82]		,     )

      a		:   Tuple	  =	tokenizer.tokenize('I was born in 92000, and this is falsé.'      )
      self.assertListEqual(
          __snake_case		,     [
              SPIECE_UNDERLINE + 'I',
              SPIECE_UNDERLINE + 'was',
              SPIECE_UNDERLINE + 'b',
              'or',
              'n',
              SPIECE_UNDERLINE + 'in',
              SPIECE_UNDERLINE + '',
              '9',
              '2',
              '0',
              '0',
              '0',
              ',',
              SPIECE_UNDERLINE + 'and',
              SPIECE_UNDERLINE + 'this',
              SPIECE_UNDERLINE + 'is',
              SPIECE_UNDERLINE + 'f',
              'al',
              's',
              'é',
              '.',
          ]		,     )
      a		:   Dict	  =	tokenizer.convert_tokens_to_ids(__snake_case      )
      self.assertListEqual(
          __snake_case		,     [8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]		,     )

      a		:   Tuple	  =	tokenizer.convert_ids_to_tokens(__snake_case      )
      self.assertListEqual(
          __snake_case		,     [
              SPIECE_UNDERLINE + 'I',
              SPIECE_UNDERLINE + 'was',
              SPIECE_UNDERLINE + 'b',
              'or',
              'n',
              SPIECE_UNDERLINE + 'in',
              SPIECE_UNDERLINE + '',
              '<unk>',
              '2',
              '0',
              '0',
              '0',
              ',',
              SPIECE_UNDERLINE + 'and',
              SPIECE_UNDERLINE + 'this',
              SPIECE_UNDERLINE + 'is',
              SPIECE_UNDERLINE + 'f',
              'al',
              's',
              '<unk>',
              '.',
          ]		,     )







    @cached_property
    def      lowercase_			( self					:    Optional[Any]      ):
      return ReformerTokenizer.from_pretrained('google/reformer-crime-and-punishment'      )







    @slow
    def      lowercase_			( self					:    Tuple      ):
      a		:   int	  =	'Hello World!'
      a		:   Optional[int]	  =	[1_26, 32, 2_62, 1_52, 38, 72, 2_87]

      self.assertListEqual(__snake_case		,     self.big_tokenizer.encode(__snake_case      )      )







    @slow
    def      lowercase_			( self					:    str      ):
      a		:   Any	  =	(
          'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
          ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
      )
      a		:   Union[str, Any]	  =	[
          1_08,
          2_65,
          24,
          1_11,
          4,
          2_58,
          1_56,
          35,
          28,
          2_75,
          3,
          2_59,
          2_97,
          2_60,
          84,
          4,
          35,
          1_10,
          44,
          8,
          2_59,
          91,
          2_68,
          21,
          11,
          2_09,
          2_74,
          1_09,
          2_66,
          2_77,
          1_17,
          86,
          93,
          3_15,
          2_58,
          2_78,
          2_58,
          2_77,
          2_58,
          0,
          2_58,
          2_88,
          2_58,
          3_19,
          2_58,
          0,
          2_58,
          0,
          2_58,
          0,
          2_58,
          0,
          2_58,
          2_87,
          2_58,
          3_15,
          2_58,
          2_89,
          2_58,
          2_78,
          99,
          2_69,
          2_66,
          2_62,
          8,
          2_59,
          2_41,
          4,
          2_17,
          2_30,
          2_68,
          2_66,
          55,
          1_68,
          1_06,
          75,
          1_93,
          2_66,
          2_23,
          27,
          49,
          26,
          2_82,
          25,
          2_64,
          2_99,
          19,
          26,
          0,
          2_58,
          2_77,
          1_17,
          86,
          93,
          1_76,
          1_83,
          2_70,
          11,
          2_62,
          42,
          61,
          2_65,
      ]

      self.assertListEqual(__snake_case		,     self.big_tokenizer.encode(__snake_case      )      )







    @require_torch
    @slow
    def      lowercase_			( self					:    Any      ):
      import torch

      from transformers import ReformerConfig, ReformerModel

      # Build sequence
      a		:   Optional[int]	  =	list(self.big_tokenizer.get_vocab().keys()      )[:10]
      a		:   List[Any]	  =	' '.join(__snake_case      )
      a		:   List[Any]	  =	self.big_tokenizer.encode_plus(__snake_case		,     return_tensors='pt'      )
      a		:   Any	  =	self.big_tokenizer.batch_encode_plus([sequence, sequence]		,     return_tensors='pt'      )

      a		:   int	  =	ReformerConfig()
      # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
      a		:   List[str]	  =	encoded_sequence['input_ids'].shape
      a		:   Optional[Any]	  =	ReformerModel(__snake_case      )

      # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
      assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

      with torch.no_grad():
        model(**__snake_case      )
        model(**__snake_case      )







    @slow
    def      lowercase_			( self					:    Tuple      ):
      # fmt: off
      a		:   str	  =	{'input_ids': [[1_08, 2_65, 24, 1_11, 4, 2_58, 1_56, 7, 51, 2_79, 58, 7, 76, 25, 69, 2_78], [1_40, 2_43, 2_64, 1_34, 17, 2_67, 77, 2_63, 22, 2_62, 2_97, 2_58, 3_04, 1_77, 2_79, 2_66, 14, 89, 13, 35, 2_61, 2_99, 2_72, 1_37, 2_75, 2_78]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
      # fmt: on

      # This tokenizer does not know some characters like ")".
      # That is the reason why we use very simple texts here.
      # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
      a		:   Optional[Any]	  =	[
          'This is a very simple sentence.',
          'The quick brown fox jumps over the lazy dog.',
      ]

      self.tokenizer_integration_test_util(
          expected_encoding=__snake_case		,     model_name='google/reformer-crime-and-punishment'		,     revision='0e6c3decb8211d49bf881013425dc8b0448b3f5a'		,     padding=__snake_case		,     sequences=__snake_case		,     )




'''simple docstring'''






import numpy as np
def  lowerCamelCase__			(		_A							):
  return 1 / (1 + np.exp(-vector							))
def  lowerCamelCase__			(		_A							):
  return vector * sigmoid(1.702 * vector							)


if __name__ == "__main__":
     import doctest

     doctest.testmod()